Multi-model Based Simulation Platform for Urban Traffic Simulation

  • Yuu Nakajima
  • Shohei Yamane
  • Hiromitsu Hattori
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7057)

Abstract

Multiagent-based simulations are regarded as a useful technology for analyzing complex social systems; for example, traffic in a city. Traffic in a city has various aspects such as route planning on the road network and driving operations on a certain road. Both types of human behavior are being studied separately by specialists in their respective domains. We believe that traffic simulation platforms should integrate the various paradigms underlying agent decision making and the target environment. We focus on urban traffic as the target problem and attempt to realize a multiagent simulation platform based on the multi-model approach. While traffic flow simulations using simple agents are popular in the traffic domain, it has been recognized that driving behavior simulations with sophisticated agents are also beneficial. However, there is no software platform that can integrate traffic simulators dealing with different aspects of urban traffic. In this paper, we propose a traffic simulation platform that can execute citywide traffic simulations that take account of the aspects of route selection on a road network and driving behavior on individual roads. The proposed simulation platform enables the multiple aspects of city traffic to be reproduced while still retaining scalability.

Keywords

Road Network Multiagent System Driving Behavior Simulation Platform Route Selection 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yuu Nakajima
    • 1
  • Shohei Yamane
    • 1
  • Hiromitsu Hattori
    • 1
  1. 1.Department of Social InformaticsKyoto UniversitySakyo-kuJapan

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